arcade-mcp/libs/arcade-core/arcade_core/schema.py
Sam Partee b6b4cd0a4c
🏗️ Restructure: Multi-Package Architecture + uv Migration (#412)
### Overview
Major restructuring from monolithic `arcade-ai` package to modular
library architecture with standardized uv-based dependency management.

![arcade-ai Monorepo
(2)](https://github.com/user-attachments/assets/25f102b0-bb87-4a04-9701-d227d05664b1)

### New Package Structure
- **`arcade-tdk`** - Lightweight toolkit development kit (core
decorators, auth)
- **`arcade-core`** - Core execution engine and catalog functionality  
- **`arcade-serve`** - FastAPI/MCP server components
- **`arcade-ai`** - Meta package that includes CLI functionality.
Optionally include evals via the `evals` extra. Optionally include all
packages via the `all` extra.

### Key Benefits
- **Lighter Dependencies**: Toolkits now depend only on `arcade-tdk` (~2
deps) vs full `arcade-ai` (~30+ deps)
- **Faster Builds**: uv provides 10-100x faster dependency resolution
and installation
- **Better Modularity**: Clear separation of concerns, consumers import
only what they need
- **Standard Tooling**: Eliminates custom poetry scripts, uses standard
Python packaging

### Migration Impact
- All 20 toolkits converted from poetry → uv with `arcade-tdk`
dependencies plus `arcade-ai[evals]` and `arcade-serve` dev
dependencies. When developing locally, devs should install toolkits via
`make install-local`.
- Modern Python 3.10+ type hints throughout
- Standardized build system with hatchling backend
- Enhanced Makefile with robust toolkit management commands
- Removed `arcade dev` CLI command
- Reduce the number of files created by `arcade new` and add an option
to not generate a tests and evals folder.

This foundation enables faster development cycles and cleaner dependency
chains for the growing toolkit ecosystem.

### Todo After this PR is merged
- [ ] Post-merge workflow(s) (release & publish containers, etc)
- [ ] Release order plan. @EricGustin suggests releasing in the
following order:
    1. `arcade-core` version 0.1.0
    2. `arcade-serve` version 0.1.0 and `arcade-tdk` version 0.1.0
    3. `arcade-ai` version 2.0.0
4. Patch release for all toolkits (all changes in toolkits are internal
refactors)
- [ ] [Update docs](https://github.com/ArcadeAI/docs/pull/318)

---------

Co-authored-by: Eric Gustin <eric@arcade.dev>
Co-authored-by: Eric Gustin <34000337+EricGustin@users.noreply.github.com>
2025-06-11 16:48:17 -07:00

441 lines
14 KiB
Python

import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Literal, Optional, Union
from pydantic import BaseModel, Field
# allow for custom tool name separator
TOOL_NAME_SEPARATOR = os.getenv("ARCADE_TOOL_NAME_SEPARATOR", ".")
class ValueSchema(BaseModel):
"""Value schema for input parameters and outputs."""
val_type: Literal["string", "integer", "number", "boolean", "json", "array"]
"""The type of the value."""
inner_val_type: Optional[Literal["string", "integer", "number", "boolean", "json"]] = None
"""The type of the inner value, if the value is a list."""
enum: Optional[list[str]] = None
"""The list of possible values for the value, if it is a closed list."""
class InputParameter(BaseModel):
"""A parameter that can be passed to a tool."""
name: str = Field(..., description="The human-readable name of this parameter.")
required: bool = Field(
...,
description="Whether this parameter is required (true) or optional (false).",
)
description: Optional[str] = Field(
None, description="A descriptive, human-readable explanation of the parameter."
)
value_schema: ValueSchema = Field(
...,
description="The schema of the value of this parameter.",
)
inferrable: bool = Field(
True,
description="Whether a value for this parameter can be inferred by a model. Defaults to `true`.",
)
class ToolInput(BaseModel):
"""The inputs that a tool accepts."""
parameters: list[InputParameter]
"""The list of parameters that the tool accepts."""
tool_context_parameter_name: str | None = Field(default=None, exclude=True)
"""
The name of the target parameter that will contain the tool context (if any).
This field will not be included in serialization.
"""
class ToolOutput(BaseModel):
"""The output of a tool."""
description: Optional[str] = Field(
None, description="A descriptive, human-readable explanation of the output."
)
available_modes: list[str] = Field(
default_factory=lambda: ["value", "error", "null"],
description="The available modes for the output.",
)
value_schema: Optional[ValueSchema] = Field(
None, description="The schema of the value of the output."
)
class OAuth2Requirement(BaseModel):
"""Indicates that the tool requires OAuth 2.0 authorization."""
scopes: Optional[list[str]] = None
"""The scope(s) needed for the authorized action."""
class ToolAuthRequirement(BaseModel):
"""A requirement for authorization to use a tool."""
# Provider ID, Type, and ID needed for the Arcade Engine to look up the auth provider.
# However, the developer generally does not need to set these directly.
# Instead, they will use:
# @tool(requires_auth=Google(scopes=["profile", "email"]))
# or
# client.auth.authorize(provider=AuthProvider.google, scopes=["profile", "email"])
#
# The Arcade SDK translates these into the appropriate provider ID (Google) and type (OAuth2).
# The only time the developer will set these is if they are using a custom auth provider.
provider_id: Optional[str] = None
"""The provider ID configured in Arcade that acts as an alias to well-known configuration."""
provider_type: str
"""The type of the authorization provider."""
id: Optional[str] = None
"""A provider's unique identifier, allowing the tool to specify a specific authorization provider. Recommended for private tools only."""
oauth2: Optional[OAuth2Requirement] = None
"""The OAuth 2.0 requirement, if any."""
class ToolSecretRequirement(BaseModel):
"""A requirement for a tool to run."""
key: str
"""The ID of the secret."""
class ToolMetadataKey(str, Enum):
"""Convience enum for commonly used metadata keys."""
CLIENT_ID = "client_id"
COORDINATOR_URL = "coordinator_url"
@staticmethod
def requires_auth(key: str) -> bool:
"""Whether the key depends on the tool having an authorization requirement."""
keys_that_require_auth = [ToolMetadataKey.CLIENT_ID]
return key.strip().lower() in keys_that_require_auth
class ToolMetadataRequirement(BaseModel):
"""A requirement for a tool to run."""
key: str
"""The ID of the metadata."""
class ToolRequirements(BaseModel):
"""The requirements for a tool to run."""
authorization: Union[ToolAuthRequirement, None] = None
"""The authorization requirements for the tool, if any."""
secrets: Union[list[ToolSecretRequirement], None] = None
"""The secret requirements for the tool, if any."""
metadata: Union[list[ToolMetadataRequirement], None] = None
"""The metadata requirements for the tool, if any."""
class ToolkitDefinition(BaseModel):
"""The specification of a toolkit."""
name: str
"""The name of the toolkit."""
description: Optional[str] = None
"""The description of the toolkit."""
version: Optional[str] = None
"""The version identifier of the toolkit."""
@dataclass(frozen=True)
class FullyQualifiedName:
"""The fully-qualified name of a tool."""
name: str
"""The name of the tool."""
toolkit_name: str
"""The name of the toolkit containing the tool."""
toolkit_version: Optional[str] = None
"""The version of the toolkit containing the tool."""
def __str__(self) -> str:
return f"{self.toolkit_name}{TOOL_NAME_SEPARATOR}{self.name}"
def __eq__(self, other: Any) -> bool:
if not isinstance(other, FullyQualifiedName):
return False
return (
self.name.lower() == other.name.lower()
and self.toolkit_name.lower() == other.toolkit_name.lower()
and (self.toolkit_version or "").lower() == (other.toolkit_version or "").lower()
)
def __hash__(self) -> int:
return hash((
self.name.lower(),
self.toolkit_name.lower(),
(self.toolkit_version or "").lower(),
))
def equals_ignoring_version(self, other: "FullyQualifiedName") -> bool:
"""Check if two fully-qualified tool names are equal, ignoring the version."""
return (
self.name.lower() == other.name.lower()
and self.toolkit_name.lower() == other.toolkit_name.lower()
)
@staticmethod
def from_toolkit(tool_name: str, toolkit: ToolkitDefinition) -> "FullyQualifiedName":
"""Creates a fully-qualified tool name from a tool name and a ToolkitDefinition."""
return FullyQualifiedName(tool_name, toolkit.name, toolkit.version)
class ToolDefinition(BaseModel):
"""The specification of a tool."""
name: str
"""The name of the tool."""
fully_qualified_name: str
"""The fully-qualified name of the tool."""
description: str
"""The description of the tool."""
toolkit: ToolkitDefinition
"""The toolkit that contains the tool."""
input: ToolInput
"""The inputs that the tool accepts."""
output: ToolOutput
"""The output types that the tool can return."""
requirements: ToolRequirements
"""The requirements (e.g. authorization) for the tool to run."""
deprecation_message: Optional[str] = None
"""The message to display when the tool is deprecated."""
def get_fully_qualified_name(self) -> FullyQualifiedName:
return FullyQualifiedName(self.name, self.toolkit.name, self.toolkit.version)
class ToolReference(BaseModel):
"""The name and version of a tool."""
name: str
"""The name of the tool."""
toolkit: str
"""The name of the toolkit containing the tool."""
version: Optional[str] = None
"""The version of the toolkit containing the tool."""
def get_fully_qualified_name(self) -> FullyQualifiedName:
return FullyQualifiedName(self.name, self.toolkit, self.version)
class ToolAuthorizationContext(BaseModel):
"""The context for a tool invocation that requires authorization."""
token: str | None = None
"""The token for the tool invocation."""
user_info: dict = Field(default={})
"""
The user information provided by the authorization server (if any).
Some providers can provide structured user info,
for example an internal provider-specific user ID.
For those providers that support retrieving user info,
the Engine can automatically pass that to tool invocations.
"""
class ToolSecretItem(BaseModel):
"""The context for a tool secret."""
key: str
"""The key of the secret."""
value: str
"""The value of the secret."""
class ToolMetadataItem(BaseModel):
"""The context for a tool metadata."""
key: str
"""The key of the metadata."""
value: str
"""The value of the metadata."""
class ToolContext(BaseModel):
"""The context for a tool invocation."""
authorization: ToolAuthorizationContext | None = None
"""The authorization context for the tool invocation that requires authorization."""
secrets: list[ToolSecretItem] | None = None
"""The secrets for the tool invocation."""
metadata: list[ToolMetadataItem] | None = None
"""The metadata for the tool invocation."""
user_id: str | None = None
"""The user ID for the tool invocation (if any)."""
def get_auth_token_or_empty(self) -> str:
"""Retrieve the authorization token, or return an empty string if not available."""
return self.authorization.token if self.authorization and self.authorization.token else ""
def get_secret(self, key: str) -> str:
"""Retrieve the secret for the tool invocation."""
return self._get_item(key, self.secrets, "secret")
def get_metadata(self, key: str) -> str:
"""Retrieve the metadata for the tool invocation."""
return self._get_item(key, self.metadata, "metadata")
def _get_item(
self, key: str, items: list[ToolMetadataItem] | list[ToolSecretItem] | None, item_name: str
) -> str:
if not key or not key.strip():
raise ValueError(
f"{item_name.capitalize()} key passed to get_{item_name} cannot be empty."
)
if not items:
raise ValueError(f"{item_name.capitalize()}s not found in context.")
normalized_key = key.lower()
for item in items:
if item.key.lower() == normalized_key:
return item.value
raise ValueError(f"{item_name.capitalize()} {key} not found in context.")
def set_secret(self, key: str, value: str) -> None:
"""Set a secret for the tool invocation."""
if not self.secrets:
self.secrets = []
secret = ToolSecretItem(key=str(key), value=str(value))
self.secrets.append(secret)
class ToolCallRequest(BaseModel):
"""The request to call (invoke) a tool."""
run_id: str | None = None
"""The globally-unique run ID provided by the Engine."""
execution_id: str | None = None
"""The globally-unique ID for this tool execution in the run."""
created_at: str | None = None
"""The timestamp when the tool invocation was created."""
tool: ToolReference
"""The fully-qualified name and version of the tool."""
inputs: dict[str, Any] | None = None
"""The inputs for the tool."""
context: ToolContext = Field(default_factory=ToolContext)
"""The context for the tool invocation."""
class ToolCallLog(BaseModel):
"""A log that occurred during the tool invocation."""
message: str
"""The user-facing warning message."""
level: Literal[
"debug",
"info",
"warning",
"error",
]
"""The level of severity for the log."""
subtype: Optional[Literal["deprecation"]] = None
"""Optional field for further categorization of the log."""
class ToolCallError(BaseModel):
"""The error that occurred during the tool invocation."""
message: str
"""The user-facing error message."""
developer_message: str | None = None
"""The developer-facing error details."""
can_retry: bool = False
"""Whether the tool call can be retried."""
additional_prompt_content: str | None = None
"""Additional content to be included in the retry prompt."""
retry_after_ms: int | None = None
"""The number of milliseconds (if any) to wait before retrying the tool call."""
traceback_info: str | None = None
"""The traceback information for the tool call."""
class ToolCallRequiresAuthorization(BaseModel):
"""The authorization requirements for the tool invocation."""
authorization_url: str | None = None
"""The URL to redirect the user to for authorization."""
authorization_id: str | None = None
"""The ID for checking the status of the authorization."""
scopes: list[str] | None = None
"""The scopes that are required for authorization."""
status: str | None = None
"""The status of the authorization."""
class ToolCallOutput(BaseModel):
"""The output of a tool invocation."""
value: Union[str, int, float, bool, dict, list[str]] | None = None
"""The value returned by the tool."""
logs: list[ToolCallLog] | None = None
"""The logs that occurred during the tool invocation."""
error: ToolCallError | None = None
"""The error that occurred during the tool invocation."""
requires_authorization: ToolCallRequiresAuthorization | None = None
"""The authorization requirements for the tool invocation."""
model_config = {
"json_schema_extra": {
"oneOf": [
{"required": ["value"]},
{"required": ["error"]},
{"required": ["requires_authorization"]},
{"required": ["artifact"]},
]
}
}
class ToolCallResponse(BaseModel):
"""The response to a tool invocation."""
execution_id: str
"""The globally-unique ID for this tool execution."""
finished_at: str
"""The timestamp when the tool execution finished."""
duration: float
"""The duration of the tool execution in milliseconds (ms)."""
success: bool
"""Whether the tool execution was successful."""
output: ToolCallOutput | None = None
"""The output of the tool invocation."""